Docker Compose에서`celeryd`와`celerybeat`을 어떻게 설정합니까?

Question

분당 업데이트 작업이 있습니다.

이것은 장고 응용 프로그램의 Dockerfile입니다.

FROM python:3-onbuild 

COPY .//
EXPOSE 8000 
RUN pip3 install -r requirements.txt 
RUN python3 manage.py collectstatic --noinput 

ENTRYPOINT ["python3", "manage.py", "celeryd"] 
ENTRYPOINT ["python3", "manage.py", "celerybeat"] 
ENTRYPOINT ["/app/start.sh"] 

이것은 내 도커 - compose.yml입니다.

version: "3" 
services: 
    nginx: 
    image: nginx:latest 
    container_name: nginx_airport 
    ports: 
     - "8080:8080" 
    volumes: 
     - ./:/app 
     - ./nginx:/etc/nginx/conf.d 
     - ./static:/app/static 
    depends_on: 
     - web 
    rabbit: 
     hostname: rabbit_airport 
     image: rabbitmq:latest 
     environment: 
      - RABBITMQ_DEFAULT_USER=admin 
      - RABBITMQ_DEFAULT_PASS=asdasdasd 
     ports: 
      - "5673:5672" 
    web: 
    build: ./ 
    container_name: django_airport 
    volumes: 
     - ./:/app 
     - ./static:/app/static 
    expose: 
     - "8080" 
    links: 
     - rabbit 
    depends_on: 
     - rabbit 

이것은 현재 실행중인 컨테이너의 맨 앞에있는 로그입니다.

rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:30 === 
rabbit_1 | Starting RabbitMQ 3.6.12 on Erlang 19.2.1 
rabbit_1 | Copyright (C) 2007-2017 Pivotal Software, Inc. 
rabbit_1 | Licensed under the MPL. See http://www.rabbitmq.com/ 
rabbit_1 | 
rabbit_1 |    RabbitMQ 3.6.12. Copyright (C) 2007-2017 Pivotal Software, Inc. 
rabbit_1 | ## ##  Licensed under the MPL. See http://www.rabbitmq.com/ 
rabbit_1 | ## ## 
rabbit_1 | ########## Logs: tty 
rabbit_1 | ###### ##  tty 
rabbit_1 | ########## 
rabbit_1 |    Starting broker... 
rabbit_1 | 
rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:30 === 
rabbit_1 | node   : rabbit@rabbit_airport 
rabbit_1 | home dir  : /var/lib/rabbitmq 
rabbit_1 | config file(s) : /etc/rabbitmq/rabbitmq.config 
rabbit_1 | cookie hash : grcK4ii6UVUYiLRYxWUffw== 
rabbit_1 | log   : tty 
rabbit_1 | sasl log  : tty 
rabbit_1 | database dir : /var/lib/rabbitmq/mnesia/rabbit@rabbit_airport 
rabbit_1 | 
rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:31 === 
rabbit_1 | Memory high watermark set to 3145 MiB (3298503884 bytes) of 7864 MiB (8246259712 bytes) total 
rabbit_1 | 
rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:31 === 
rabbit_1 | Enabling free disk space monitoring 
rabbit_1 | 
rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:31 === 
rabbit_1 | Disk free limit set to 50MB 
rabbit_1 | 
rabbit_1 | =INFO REPORT==== 29-Sep-2017::11:45:31 === 
rabbit_1 | Limiting to approx 1048476 file handles (943626 sockets) 

셀러리 작업이 실행되고 있지 않은 것을 제외하면 모두 괜찮습니다.

편집 :

#!/bin/bash 

# PENDING: From the source here, 
# http://tutos.readthedocs.io/en/latest/source/ndg.html it says that it is a 
# common practice to have a specific user to handle the webserver. 

SCRIPT=$(readlink -f "$0") 
DJANGO_SETTINGS_MODULE=airport.settings 
DJANGO_WSGI_MODULE=airport.wsgi 
NAME="airport" 
NUM_WORKERS=3 

if [ "$BASEDIR" = "/" ] 
then 
    BASEDIR="" 
else 
    BASEDIR=$(dirname "$SCRIPT") 
fi 

if [ "$BASEDIR" = "/" ] 
then 
    VENV_BIN="venv/bin" 
    SOCKFILE="run/gunicorn.sock" 
else 
    VENV_BIN=${BASEDIR}"/venv/bin" 
    SOCKFILE=${BASEDIR}"/run/gunicorn.sock" 
fi 

SOCKFILEDIR="$(dirname "$SOCKFILE")" 
VENV_ACTIVATE=${VENV_BIN}"/activate" 
VENV_GUNICORN=${VENV_BIN}"/gunicorn" 

# Activate the virtual environment. 
# Only set this for virtual environment. 
#cd $BASEDIR 
#source $VENV_ACTIVATE 

# Set environment variables. 
export DJANGO_SETTINGS_MODULE=$DJANGO_SETTINGS_MODULE 
export PYTHONPATH=$PYTHONPATH:$BASEDIR 

# Create run directory if they does not exists. 
#test -d $SOCKFILEDIR || mkdir -p $SOCKFILEDIR 

# Start Gunicorn! 
# Programs meant to be run under supervisor should not daemonize themselves 
# (do not use --daemon). 
# 
# Set this for virtual environment. 
#exec ${VENV_GUNICORN} ${DJANGO_WSGI_MODULE}:application \ 
# --bind=unix:$SOCKFILE \ 
# --name $NAME \ 
# --workers $NUM_WORKERS 

# For non-virtual environment. 
exec gunicorn ${DJANGO_WSGI_MODULE}:application \ 
    --bind=unix:$SOCKFILE \ 
    --name $NAME \ 
    --workers $NUM_WORKERS 

DetailsDetailsDetailsDetailsDetails DetailsDetailsDetailsDetailsDetails DetailsDetailsDetailsDetailsDetails DetailsDetailsDetailsDetailsDetails DetailsDetailsDetailsDetailsDetails DetailsDetailsDetailsDetailsDetails

Answer 1

귀하의 진입 점은 서로를 무시한다. 마지막 엔트리 포인트 만 실행됩니다. 다음을 빌드하고 실행하여 확실하게 시도 할 수 있습니다. docker docs 한 바와 같이

FROM alpine 
ENTRYPOINT ["echo", "1"] 
ENTRYPOINT ["echo", "2"] 

. 컨테이너 당 여러 서비스를 시작하려면 래퍼 스크립트에서 시작 명령을 래핑하고 dockerfile에서 CMD 내부에서 래퍼 스크립트를 실행할 수 있습니다.

wrapper.sh

python3 manage.py celeryd 
python3 manage.py celerybeat 
./app/start.sh 

---

FROM python:3-onbuild 

COPY .//
EXPOSE 8000 
RUN pip3 install -r requirements.txt 
RUN python3 manage.py collectstatic --noinput 
ADD wrapper.sh wrapper.sh 
CMD ./wrapper.sh